Reconstruction of apparent orthotropic conductivity tensor image using magnetic resonance electrical impedance tomography
Abstract
Magnetic resonance electrical impedance tomography visualizes current density and/or conductivity distributions inside an electrically conductive object. Injecting currents into the imaging object along at least two different directions, induced magnetic flux density data can be measured using a magnetic resonance imaging scanner. Without rotating the object inside the scanner, we can measure only one component of the magnetic flux density denoted as B{sub z}. Since the biological tissues such as skeletal muscle and brain white matter show strong anisotropic properties, the reconstruction of anisotropic conductivity tensor is indispensable for the accurate observations in the biological systems. In this paper, we propose a direct method to reconstruct an axial apparent orthotropic conductivity tensor by using multiple B{sub z} data subject to multiple injection currents. To investigate the anisotropic conductivity properties, we first recover the internal current density from the measured B{sub z} data. From the recovered internal current density and the curlfree condition of the electric field, we derive an overdetermined matrix system for determining the internal absolute orthotropic conductivity tensor. The overdetermined matrix system is designed to use a combination of two loops around each pixel. Numerical simulations and phantom experimental results demonstrate that the proposed algorithm stably determines themore »
 Authors:
 Department of Biomedical Engineering, Kyung Hee University, Yongin, Gyeonggi (Korea, Republic of)
 Department of Mathematics, Konkuk University, Seoul (Korea, Republic of)
 Publication Date:
 OSTI Identifier:
 22399264
 Resource Type:
 Journal Article
 Resource Relation:
 Journal Name: Journal of Applied Physics; Journal Volume: 117; Journal Issue: 10; Other Information: (c) 2015 AIP Publishing LLC; Country of input: International Atomic Energy Agency (IAEA)
 Country of Publication:
 United States
 Language:
 English
 Subject:
 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; ALGORITHMS; ANISOTROPY; COMPUTERIZED SIMULATION; CURRENT DENSITY; ELECTRIC CONDUCTIVITY; ELECTRIC CURRENTS; ELECTRIC FIELDS; FLUX DENSITY; IMPEDANCE; MAGNETIC FLUX; MAGNETIC RESONANCE; NMR IMAGING; PHANTOMS; TENSORS; TOMOGRAPHY
Citation Formats
Sajib, Saurav Z. K., Kim, Ji Eun, Jeong, Woo Chul, Kim, Hyung Joong, Woo, Eung Je, and Kwon, Oh In, Email: oikwon@konkuk.ac.kr. Reconstruction of apparent orthotropic conductivity tensor image using magnetic resonance electrical impedance tomography. United States: N. p., 2015.
Web. doi:10.1063/1.4914904.
Sajib, Saurav Z. K., Kim, Ji Eun, Jeong, Woo Chul, Kim, Hyung Joong, Woo, Eung Je, & Kwon, Oh In, Email: oikwon@konkuk.ac.kr. Reconstruction of apparent orthotropic conductivity tensor image using magnetic resonance electrical impedance tomography. United States. doi:10.1063/1.4914904.
Sajib, Saurav Z. K., Kim, Ji Eun, Jeong, Woo Chul, Kim, Hyung Joong, Woo, Eung Je, and Kwon, Oh In, Email: oikwon@konkuk.ac.kr. 2015.
"Reconstruction of apparent orthotropic conductivity tensor image using magnetic resonance electrical impedance tomography". United States.
doi:10.1063/1.4914904.
@article{osti_22399264,
title = {Reconstruction of apparent orthotropic conductivity tensor image using magnetic resonance electrical impedance tomography},
author = {Sajib, Saurav Z. K. and Kim, Ji Eun and Jeong, Woo Chul and Kim, Hyung Joong and Woo, Eung Je and Kwon, Oh In, Email: oikwon@konkuk.ac.kr},
abstractNote = {Magnetic resonance electrical impedance tomography visualizes current density and/or conductivity distributions inside an electrically conductive object. Injecting currents into the imaging object along at least two different directions, induced magnetic flux density data can be measured using a magnetic resonance imaging scanner. Without rotating the object inside the scanner, we can measure only one component of the magnetic flux density denoted as B{sub z}. Since the biological tissues such as skeletal muscle and brain white matter show strong anisotropic properties, the reconstruction of anisotropic conductivity tensor is indispensable for the accurate observations in the biological systems. In this paper, we propose a direct method to reconstruct an axial apparent orthotropic conductivity tensor by using multiple B{sub z} data subject to multiple injection currents. To investigate the anisotropic conductivity properties, we first recover the internal current density from the measured B{sub z} data. From the recovered internal current density and the curlfree condition of the electric field, we derive an overdetermined matrix system for determining the internal absolute orthotropic conductivity tensor. The overdetermined matrix system is designed to use a combination of two loops around each pixel. Numerical simulations and phantom experimental results demonstrate that the proposed algorithm stably determines the orthotropic conductivity tensor.},
doi = {10.1063/1.4914904},
journal = {Journal of Applied Physics},
number = 10,
volume = 117,
place = {United States},
year = 2015,
month = 3
}

Anisotropy of biological tissues is a lowfrequency phenomenon that is associated with the function and structure of cell membranes. Imaging of anisotropic conductivity has potential for the analysis of interactions between electromagnetic fields and biological systems, such as the prediction of current pathways in electrical stimulation therapy. To improve application to the clinical environment, precise approaches are required to understand the exact responses inside the human body subjected to the stimulated currents. In this study, we experimentally evaluate the anisotropic conductivity tensor distribution of canine brain tissues, using a recently developed diffusion tensormagnetic resonance electrical impedance tomography method. At lowmore »

Submillimeter resolution electrical conductivity images of brain tissues using magnetic resonancebased electrical impedance tomography
Recent magnetic resonance (MR)based electrical impedance tomography (MREIT) of in vivo animal and human subjects enabled the imaging of electromagnetic properties, such as conductivity and permittivity, on tissue structure and function with a few millimeter pixel size. At those resolutions, the conductivity contrast might be sufficient to distinguish different tissue type for certain applications. Since the precise measurement of electrical conductivity under the tissue levels can provide alternative information in a wide range of biomedical applications, it is necessary to develop highresolution MREIT technique to enhance its availability. In this study, we provide the experimental evaluation of submillimeter resolution conductivitymore » 
A neural network image reconstruction technique for electrical impedance tomography
Reconstruction of Images in Electrical Impedance Tomography requires the solution of a nonlinear inverse problem on noisy data. This problem is typically illconditioned and requires either simplifying assumptions or regularization based on a priori knowledge. This paper presents a reconstruction algorithm using neural network techniques which calculates a linear approximation of the inverse problem directly from finite element simulations of the forward problem. This inverse is adapted to the geometry of the medium and the signaltonoise ratio (SNR) used during network training. Results show good conductivity reconstruction where measurement SNR is similar to the training conditions. The advantages of thismore » 
Prospective comparison of computed tomography and magnetic resonance imaging for liver cancer delineation using deformable image registration
Purpose: The aim of this study was to compare magnetic resonance imaging (MRI) with computed tomography (CT) for liver cancer tumor definition for highprecision radiotherapy planning. Methods and Materials: Diagnostic quality MRI scans and triphasic CT scans, with the liver immobilized in exhale, were obtained at the time of radiation planning for 26 patients with unresectable liver metastases (n = 8), hepatocellular carcinoma (n = 10), and cholangiocarcinoma (n = 8). On the CT and MRI series best demonstrating the tumor, the liver and gross tumor volumes (GTVs) were contoured, and intrahepatic anatomic reference points were identified. Deformable registration wasmore » 
Denoising of B{sub 1}{sup +} field maps for noiserobust image reconstruction in electrical properties tomography
Purpose: To validate the use of adaptive nonlinear filters in reconstructing conductivity and permittivity images from the noisy B{sub 1}{sup +} maps in electrical properties tomography (EPT). Methods: In EPT, electrical property images are computed by taking Laplacian of the B{sub 1}{sup +} maps. To mitigate the noise amplification in computing the Laplacian, the authors applied adaptive nonlinear denoising filters to the measured complex B{sub 1}{sup +} maps. After the denoising process, they computed the Laplacian by central differences. They performed EPT experiments on phantoms and a human brain at 3 T along with corresponding EPT simulations on finitedifference timedomainmore »